Semantic Search in E-Tourism Services: Making Data Compilation Easier

  • Juhi  Agarwal
  • Nishkarsh  Sharma
  • Pratik  Kumar
  • Vishesh  Parshav
  • Anubhav  Srivastava
  • Rohit  Rathore
  • R. H. Goudar
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 236)

Abstract

After the advancement of the internet technology, user can get any information on tourism. Tourism is the world’s largest and fastest growing industry. It contains so many things like accommodation, food, events, transportation package, etc. So information must be reliable because tourism product is intangible in nature. Customer cannot physically evaluate the service until he/she physically experienced but there are some areas where a greater measure of intelligence is required. The Semantic Web did a lot of work to enhance the Web by enriching its content with semantic data. E-Tourism is a good candidate for such enrichment, since it is an information-based business. In this paper, we are constructing E-Tourism ontology to provide intelligent tourism service. The algorithm is designed to integrate data from different reliable sources and structure properly in tourism knowledge base for efficiently searching the data.

Keywords

Semantic web Ontology SPARQL 

References

  1. 1.
    Yan, Z.: Ontology and semantic management system: state-of-the-arts analysis. In: Proccedings of the IADIS International Conference, ISBN: 978-972-8924-44-7, pp. 111–115 (2007)Google Scholar
  2. 2.
    Werther, H.: Intelligent systems in travel and tourism. IEEE Intell. Syst. 17(6) (2003)Google Scholar
  3. 3.
    Park, H., Yoon, A., Kwon H.-C.: Task model and task ontology for intelligent tourist information service. Int. J. u- e- Serv. Sci. Technol. 5(2), 47–58 (2012)Google Scholar
  4. 4.
    Cardoso, J.: Developing dynamic packaging systems using semantic web technologies. Trans. Inf. Sci. Appl. 3(4), 729–736 (2006)MathSciNetGoogle Scholar
  5. 5.
    Mohsin, A.: Tourist attitudes and destination marketing—the case of Australia’s Northern Territory and Malaysia. Tourism Manag. 26, 723–732 (2005)Google Scholar
  6. 6.
    Jun, S.H., Vogt, C.A., MacKay, K.J.: Relationships between travel information search an travel product purchase in pretrip contexts. J. Travel Res. 45(3), 266–274 (2007)CrossRefGoogle Scholar
  7. 7.
    Daramola, O., Adigun, M., Ayo, C.: Building an ontology-based framework for tourism recommendation services. Information and Communication Technologies in Tourism, Amsterdam, pp. 135–147 (2009)Google Scholar
  8. 8.
    Zhou, L., Zhang, D.: An ontology-supported misinformation model: toward a digital misinformaton library. IEEE Trans. Syst. Man Cybern. A. Syst. Humans 37(5), 804–813 (2007)CrossRefGoogle Scholar
  9. 9.
    Damljanovic, D., Devedzic, V.: Applying Semantic Web to E-tourism. Chapter X, Springer, Berlin, pp. 243–263 (1993)Google Scholar

Copyright information

© Springer India 2014

Authors and Affiliations

  • Juhi  Agarwal
    • 1
  • Nishkarsh  Sharma
    • 1
  • Pratik  Kumar
    • 1
  • Vishesh  Parshav
    • 1
  • Anubhav  Srivastava
    • 1
  • Rohit  Rathore
    • 1
  • R. H. Goudar
    • 1
  1. 1.Graphic Era UniversityDehradunIndia

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